Insights on AI and Recruitment
New research shows humans follow AI bias up to 90% of the time. The solution isn't removing AI — it's rethinking what human oversight actually means.
Researchers at the University of Washington found that human decision-makers followed AI biases up to 90% of the time. The findings challenge the assumption that human-in-the-loop oversight is sufficient to prevent algorithmic discrimination in hiring.
Ontario employers with 25+ employees must now disclose AI use in job postings. Here's what the new rules require and how to build compliant, governed hiring processes.
As of January 1, 2026, Ontario employers with 25 or more employees face new requirements for job postings and hiring practices. Among them: mandatory disclosure when artificial intelligence is used to screen, assess, or select candidates.
Illinois and Texas AI hiring laws took effect January 2026. Colorado's follows in June. Here's what talent acquisition teams need to know about compliance, disclosure, and AI governance.
As of January 1, 2026, talent acquisition teams using AI for hiring in Illinois or Texas face new legal requirements — and Colorado's comprehensive AI law takes effect June 30. Here's what HR leaders need to know about compliance, disclosure, and AI governance.
68% of employees use unauthorized AI tools at work. In talent acquisition, that's a compliance crisis hiding in plain sight.
The debate about whether to adopt AI in hiring is already over. Your team made the decision for you. According to ISACA's 2024 AI Pulse Poll, 68% of employees use AI tools at work that haven't been approved by their organization.
Why the leading voice on workforce transformation says caution is now HR's biggest risk—and what it means for talent acquisition.
Joseph Fuller of Harvard Business School argues that HR's instinct for caution has become a liability in the AI era. His research on workforce transformation has direct implications for talent acquisition leaders evaluating AI tools.
Why the latest frontier AI research validates human-in-the-loop approaches—and what it means for the future of talent acquisition.
Anthropic's research on AI introspection has direct implications for HR leaders evaluating AI hiring tools. If AI systems can only reliably introspect on their own reasoning 20% of the time, what does that mean for automated scoring and candidate evaluation?